Analisis Pola Pembelian dan Penjualan Bisnis Menggunakan Algoritma Apriori dalam Studi Market Basket

Analisis Pola Pembelian dan Penjualan Bisnis Menggunakan Algoritma Apriori dalam Studi Market Basket

  • ketut widya kayohana universitas bumigora
  • M Danang Samudra
  • Ni Luh Putu Febiyanti
  • Eka Fujiastuti
  • Ni komang dewani


Using the Apriori Algorima to helps optimize product placement, increase cross-selling opportunities, and improve inventory management and promotions. In-depth insights into purchase patterns can enhance sales, customer satisfaction, and operational efficiency.

Enhancing cross-selling strategies: By understanding associations between items purchased together, this research provides insights for improving cross-selling strategies. Businesses can offer relevant product recommendations, whether through in-store placement or online suggestions, to boost sales and enhance the shopping experience. The Apriori method and algorithm are used in analyzing the buying and selling of market baskets.

The research findings revealed a significant association between customers who purchase Bread and Coffee together. Support "toast" and "coffee" is 0.023666, which means that 2.3666% of the total 30 transactions includes both itemsets, confidence "toast → coffee" is 0.704403, which means that if customers buy "toast", chances are they also buy "coffee" by 70.4403%, lift "toast → coffee" is 1.472431, which shows that the probability of buying "coffee" increases by 1.472431 times if the customer also buys "toast. This presents an opportunity for businesses to improve sales through strategic product placement, promotions or special offers involving the combination of Bread and Coffee, and optimizing inventory to meet the demand of customers who tend to purchase both items simultaneously


1] A. R. Riszky and M. Sadikin, “Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan,” Jurnal Teknologi dan Sistem Komputer, vol. 7, no. 3, pp. 103–108, Jul. 2019, doi: 10.14710/jtsiskom.7.3.2019.103-108.
[2] D. Listriani, A. H. Setyaningrum, and F. Eka, “PENERAPAN METODE ASOSIASI MENGGUNAKAN ALGORITMA APRIORI PADA APLIKASI ANALISA POLA BELANJA KONSUMEN (Studi Kasus Toko Buku Gramedia Bintaro),” vol. 9, no. 2.
[3] X. Yuan, “An improved Apriori algorithm for mining association rules,” in AIP Conference Proceedings, American Institute of Physics Inc., Mar. 2017. doi: 10.1063/1.4977361.
[4] J. Jha and L. Ragha, “Educational Data Mining using Improved Apriori Algorithm,” 2013. [Online]. Available:
[5] P. Bist and A. Prambudi, “Implementation Of Data Mining On Glasses Sales Using The Apriori Algorithm,” International Journal of Cyber and IT Service Management (IJCITSM), vol. 1, no. 2, pp. 159–172, 2021, doi: 10.34306/ijcitsm.v1i1.46.